{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:7SIOZWU5ALV4BGRVKNI5XEHLFM","short_pith_number":"pith:7SIOZWU5","canonical_record":{"source":{"id":"1803.00338","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2018-03-01T12:30:22Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"b02b5419e4c869c4b70aff3b5d40dc300d95f05772dbc57c6ddee80806bc3ac4","abstract_canon_sha256":"0a105bee468c893e617045bd34bdc782bf3dbd0080d51dacd8fad43a4b538e41"},"schema_version":"1.0"},"canonical_sha256":"fc90ecda9d02ebc09a355351db90eb2b27be877f71f3e64570ab123f05c665c3","source":{"kind":"arxiv","id":"1803.00338","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.00338","created_at":"2026-05-18T00:18:25Z"},{"alias_kind":"arxiv_version","alias_value":"1803.00338v2","created_at":"2026-05-18T00:18:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.00338","created_at":"2026-05-18T00:18:25Z"},{"alias_kind":"pith_short_12","alias_value":"7SIOZWU5ALV4","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_16","alias_value":"7SIOZWU5ALV4BGRV","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_8","alias_value":"7SIOZWU5","created_at":"2026-05-18T12:32:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:7SIOZWU5ALV4BGRVKNI5XEHLFM","target":"record","payload":{"canonical_record":{"source":{"id":"1803.00338","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2018-03-01T12:30:22Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"b02b5419e4c869c4b70aff3b5d40dc300d95f05772dbc57c6ddee80806bc3ac4","abstract_canon_sha256":"0a105bee468c893e617045bd34bdc782bf3dbd0080d51dacd8fad43a4b538e41"},"schema_version":"1.0"},"canonical_sha256":"fc90ecda9d02ebc09a355351db90eb2b27be877f71f3e64570ab123f05c665c3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:18:25.190225Z","signature_b64":"Se5TNHQJNrzOGUy7lM8qLTq6G7MwNetg6rPKV/xjgHVE6tjIkyo6vyP94MN4BDEaf7WM04UKCMFtfeO6ljU/Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fc90ecda9d02ebc09a355351db90eb2b27be877f71f3e64570ab123f05c665c3","last_reissued_at":"2026-05-18T00:18:25.189659Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:18:25.189659Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1803.00338","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:18:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KXn9rQ4yASGIAaZrPUlb82kXcSbeUhyYs4GA8s3LFnwP/xGk1PhLe0q4wo4S3h158qX79v064iRpVmIapPICCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T13:53:22.801970Z"},"content_sha256":"75f15046673755a1769ca6dd9c4342f95270943ae46e02edf2e746a43200c7cf","schema_version":"1.0","event_id":"sha256:75f15046673755a1769ca6dd9c4342f95270943ae46e02edf2e746a43200c7cf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:7SIOZWU5ALV4BGRVKNI5XEHLFM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Synthesizing realistic neural population activity patterns using Generative Adversarial Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NE"],"primary_cat":"q-bio.NC","authors_text":"Arno Onken, Eugenio Piasini, Manuel Molano-Mazon, Stefano Panzeri","submitted_at":"2018-03-01T12:30:22Z","abstract_excerpt":"The ability to synthesize realistic patterns of neural activity is crucial for studying neural information processing. Here we used the Generative Adversarial Networks (GANs) framework to simulate the concerted activity of a population of neurons. We adapted the Wasserstein-GAN variant to facilitate the generation of unconstrained neural population activity patterns while still benefiting from parameter sharing in the temporal domain. We demonstrate that our proposed GAN, which we termed Spike-GAN, generates spike trains that match accurately the first- and second-order statistics of datasets "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.00338","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:18:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0hLUB03ZsFuBhjMAVvsPKA4zZuM0UUBG1FWNTMXwZ3YEA1hYx0lGqa5hSn8HlHHA61L2vGYwe2wM2fqD4xPdCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T13:53:22.802329Z"},"content_sha256":"f2d6586e8c96276c04985044338f609e8dd20cff392723da60cb09db2a8f8285","schema_version":"1.0","event_id":"sha256:f2d6586e8c96276c04985044338f609e8dd20cff392723da60cb09db2a8f8285"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7SIOZWU5ALV4BGRVKNI5XEHLFM/bundle.json","state_url":"https://pith.science/pith/7SIOZWU5ALV4BGRVKNI5XEHLFM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7SIOZWU5ALV4BGRVKNI5XEHLFM/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-30T13:53:22Z","links":{"resolver":"https://pith.science/pith/7SIOZWU5ALV4BGRVKNI5XEHLFM","bundle":"https://pith.science/pith/7SIOZWU5ALV4BGRVKNI5XEHLFM/bundle.json","state":"https://pith.science/pith/7SIOZWU5ALV4BGRVKNI5XEHLFM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7SIOZWU5ALV4BGRVKNI5XEHLFM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:7SIOZWU5ALV4BGRVKNI5XEHLFM","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"0a105bee468c893e617045bd34bdc782bf3dbd0080d51dacd8fad43a4b538e41","cross_cats_sorted":["cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2018-03-01T12:30:22Z","title_canon_sha256":"b02b5419e4c869c4b70aff3b5d40dc300d95f05772dbc57c6ddee80806bc3ac4"},"schema_version":"1.0","source":{"id":"1803.00338","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.00338","created_at":"2026-05-18T00:18:25Z"},{"alias_kind":"arxiv_version","alias_value":"1803.00338v2","created_at":"2026-05-18T00:18:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.00338","created_at":"2026-05-18T00:18:25Z"},{"alias_kind":"pith_short_12","alias_value":"7SIOZWU5ALV4","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_16","alias_value":"7SIOZWU5ALV4BGRV","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_8","alias_value":"7SIOZWU5","created_at":"2026-05-18T12:32:11Z"}],"graph_snapshots":[{"event_id":"sha256:f2d6586e8c96276c04985044338f609e8dd20cff392723da60cb09db2a8f8285","target":"graph","created_at":"2026-05-18T00:18:25Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"The ability to synthesize realistic patterns of neural activity is crucial for studying neural information processing. Here we used the Generative Adversarial Networks (GANs) framework to simulate the concerted activity of a population of neurons. We adapted the Wasserstein-GAN variant to facilitate the generation of unconstrained neural population activity patterns while still benefiting from parameter sharing in the temporal domain. We demonstrate that our proposed GAN, which we termed Spike-GAN, generates spike trains that match accurately the first- and second-order statistics of datasets ","authors_text":"Arno Onken, Eugenio Piasini, Manuel Molano-Mazon, Stefano Panzeri","cross_cats":["cs.NE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2018-03-01T12:30:22Z","title":"Synthesizing realistic neural population activity patterns using Generative Adversarial Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.00338","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:75f15046673755a1769ca6dd9c4342f95270943ae46e02edf2e746a43200c7cf","target":"record","created_at":"2026-05-18T00:18:25Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"0a105bee468c893e617045bd34bdc782bf3dbd0080d51dacd8fad43a4b538e41","cross_cats_sorted":["cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2018-03-01T12:30:22Z","title_canon_sha256":"b02b5419e4c869c4b70aff3b5d40dc300d95f05772dbc57c6ddee80806bc3ac4"},"schema_version":"1.0","source":{"id":"1803.00338","kind":"arxiv","version":2}},"canonical_sha256":"fc90ecda9d02ebc09a355351db90eb2b27be877f71f3e64570ab123f05c665c3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fc90ecda9d02ebc09a355351db90eb2b27be877f71f3e64570ab123f05c665c3","first_computed_at":"2026-05-18T00:18:25.189659Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:18:25.189659Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Se5TNHQJNrzOGUy7lM8qLTq6G7MwNetg6rPKV/xjgHVE6tjIkyo6vyP94MN4BDEaf7WM04UKCMFtfeO6ljU/Aw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:18:25.190225Z","signed_message":"canonical_sha256_bytes"},"source_id":"1803.00338","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:75f15046673755a1769ca6dd9c4342f95270943ae46e02edf2e746a43200c7cf","sha256:f2d6586e8c96276c04985044338f609e8dd20cff392723da60cb09db2a8f8285"],"state_sha256":"dd2b338c54072452d97ea1732ecf358a64864ea1684f2edd872142fd9ad2dc43"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZS8HoIDbpD0AZE//pfjK+GarT0++5762nV6OGUA+MhN+l3dR+nzPn4Uy1f45JNYW2b84S8imHTCvcMIyIPjbAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T13:53:22.804496Z","bundle_sha256":"5a7b1c9c93d6cbb7278b9b89c4bb37a6b3e3d6631b53b776d822c5094ed7ea72"}}